Triple
T27336943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Épinay-sur-Seine |
E689978
|
entity |
| Predicate | hasCinemaHistory |
P125495
|
FINISHED |
| Object | Épinay Studios |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Épinay Studios | Statement: [Épinay-sur-Seine, hasCinemaHistory, Épinay Studios]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCinemaHistory Context triple: [Épinay-sur-Seine, hasCinemaHistory, Épinay Studios]
-
A.
hasFilmExperience
Indicates that an entity has prior involvement or participation in film-related activities or productions.
-
B.
hasFilmScreenings
Indicates that a film is scheduled to be shown at one or more specific screenings or venues.
-
C.
hasPartInFilmHistory
chosen
Indicates that an entity has played a role or contributed in some way to the history or development of film.
-
D.
hasMovieTheater
Indicates that one entity possesses, contains, or includes a movie theater as part of its facilities or attributes.
-
E.
hasTheatricalFilm
Indicates that an entity has an associated theatrical film adaptation, version, or release.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ef355e5b388190a8fc1eba9b4a6656 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f69383222c81909d8baa04129d5c81 |
completed | May 3, 2026, 12:14 a.m. |
| PD | Predicate disambiguation | batch_69f690eb1e948190aab41a89969519a5 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 27, 2026, 11:41 a.m.